Interpretive Summary: The United States Nutrition Labeling and Education Act (N.L.E.A.) requires that the amount of total dietary fiber in a food product be included on the nutrition label. Dietary fiber is one of the most difficult and time consuming nutrients to measure. Near-infrared (NIR) reflectance spectroscopy, which measures the amount of light energy reflected by a substance, is a very rapid and accurate method of measuring constituents o materials without requiring extensive sample preparation, or creating chemical waste. In a previous publication from this laboratory it was demonstrated that NIR reflectance spectroscopy could be used to accurately predict the dietary fiber content of a wide range of cereal products. This study continues the previous study by expanding the calibration for dietary fiber to include cereal products with large amounts of sugar (for example sugar coated breakfast cereals, some granolas, muesli and many other types of breakfast cereals). The calibration was expanded to include high sugar products while maintaining a level of precision similar to the original calibration. The NIR method reduces the time required to measure dietary fiber in cereal products from 2-3 days to a few minutes and will benefit not only the cereal product industry but agencies responsible for monitoring industry compliance with the N.L.E.A.

Technical Abstract:
A number of cereal products contain significant amounts of sugar, often in the crystalline form. Crystalline sugar has unique spectral characteristics which have a profound influence on near-infrared determination of product composition. This study investigated the potential of expanding a near-infrared (NIR) spectroscopic calibration for the prediction of total dietary fiber in cereal products, to include products with high sugar and crystalline sugar content. As described previously (Kays et al., J. Agric. Food Chem., 44:2266-71,1996), a partial least squares NIR model was developed to predict total dietary fiber in dry milled cereal products (n=77) using AOAC procedure 991.43 as the reference method (range in total dietary fiber 0-52%). Model standard error of cross validation (SECV), multiple coefficient of determination, standard error of performance (SEP), and coefficient of determination (using n=30 independent tvalidation samples) were 1.64%, 0.99, 1.39%, and 0.99, respectively. Usin a selection algorithm to choose representative samples, an expanded model was developed with the original calibration samples (n=77) plus high sugar samples (n=39, >20% sugar). The resulting SECV and multiple coefficient of determination were 1.88% and 0.98, respectively. The model was validated using the original validation samples (n=30) plus 15 high sugar independent validation samples. The SEP was 1.40% and coefficient of determination 0.99. This study demonstrates that the NIR model for prediction of total dietary fiber in cereal and grain products can be expanded to include samples with high sugar and crystalline sugar content. Product constituents influencing model development are examined.